1. Field of the Invention
The present invention relates to an apparatus, a method and a computer program product for translating a speech input using an example and outputting the translation result.
2. Description of the Related Art
In recent years, a speech translation apparatus for supporting the communication between persons speaking different mother tongues has been expected to find practical application. Basically, this speech translation apparatus sequentially executes the speech recognition process, the translation process and the speech synthesis process using a means for recognizing the speech, a means for translating a character string obtained by speech recognition, and a means for synthesizing a speech from the character string obtained by translation.
A speech recognition system for recognizing the speech uttered by the user and outputting the character information is already used for practical purposes in the form of package software or the like. Also, a machine translation system with a written language (text) input thereto similarly finds applications in the form of package software or the like. A speech synthesis system is also in practical use. By appropriately using these software products, a speech translation apparatus can be realized.
Under the circumstances, however, speech recognition 100% in accuracy is difficult to achieve. Even the machine translation of a written language encounters the problem that since a source language may contain the ambiguity of a translation word or dependency, the translation result may not be output as intended. Also, the sentence input by speech is often not grammatically correct, so that the speech is recognized erroneously, resulting in the machine translation of an input containing an error. For these reasons, a speech translation apparatus having a practical value has yet to be realized.
Especially, a speaker of a source language unable to understand a target language cannot confirm whether the speech translation apparatus outputs the translation result as intended by the speaker, and therefore some countermeasure against the error or ambiguity of analysis in speech recognition and machine translation is essential.
The machine translation is the conversion of a sentence in a source language (Japanese, for example) into a target language (English, for example), and according to the conversion scheme, classified roughly into the rule-based machine translation, the statistical machine translation, and the example-based machine translation.
The rule-based translation apparatus includes a morphological analysis unit and a structure parsing unit, in which the sentence structure of the source language is analyzed and based on this structure, converted (transferred) into a sentence structure of the target language. The processing knowledge for structure parsing and transfer are registered in the form of rules in advance, and the translation apparatus executes the translation process by interpreting the rule. Most of the machine translation systems finding applications in package software are of this type.
The rule-based machine translation requires the preparation of a vast amount of rules for realizing a practicable, high-accuracy machine translation. The manual preparation of these rules takes a very high cost. In order to solve these problems, an idea of the statistical machine translation is proposed, and the research and development efforts have since been made vigorously.
In the statistical machine translation, the sentences in a source language and corresponding sentences in a target language are prepared in large scale (called a parallel corpus), and from this corpus, the conversion rule for translation and the probability value thereof are determined. This approach uses conversion rule having the highest probability for translation. Currently, a prototype system of speech translation using the statistical machine translation is constructed.
The example-based machine translation, on the other hand, like the statistical machine translation, uses a parallel corpus of a source language and a target language. The parallel corpus is searched for a sentence in the source language similar to the input sentence, and the sentence in the target language corresponding to the detected sentence in the source language is determined as a translation result. The rule-based machine translation and the statistical machine translation are liable to cause an ambiguity in the application of a conversion rule, with the result that a translation result departing from the intention of the speaker of the source language may be unavoidably output.
The example-based machine translation, in contrast, uses a translation corresponding to the source language sentence detected from the parallel corpus is used as it is, and the source language sentence detected by search can be confirmed by the source language speaker. Also, since the sentences of the target language are prepared manually in advance, the chance of an error occurring in the translation process is comparatively small. Nevertheless, the parallel corpus, though prepared in large scale, cannot cover all the sentences that may be input. In the example-based machine translation, the translation fails if an example similar to the input sentence cannot be retrieved. The example-based machine translation, therefore, is required to be used in complementary fashion with the rule-based machine translation and the statistical machine translation to cover wide applications.
As long as a source language sentence similar to an input sentence can be retrieved from the parallelcorpus in the example-based machine translation, the possibility of correct translation is increased. A given source language sentence, however, is not always accompanied by only one translation, and depending on the situation or context of the conversation, is required to be translated in different way. Specifically, even when an example is prepared manually, the translation may contain an ambiguity. In such a case, a method is available in which the user selects an appropriate one of a plurality of translations proposed. The speaker of the source language who cannot understand the target language, however, is unable to select an appropriate translation.
In view of this, a translation apparatus has been proposed which has the function to display a comment enabling the speaker having no knowledge of the target language to select a correct translation from the source language by displaying the language information on the translation is displayed in the source language (Japanese Patent Application Laid-open (JP-A) No. H05-128150, for example).
Specifically, when an English sentence constituting a source language including a word having a plurality of meanings (usage) is translated into Japanese and a plurality of translation candidates in Japanese are generated, for example, each translation candidate is displayed with a corresponding example of English sentence containing a word of the same usage as in the translation thereof. The speaker then selects an example sentence of the same usage as that of the source language sentence, so that a correct Japanese translation can be selected as a sentence corresponding to the selected example sentence.
In the method disclosed in JP-A No. H05-128150, however, a correct translation is required to be estimated by referring to the language information including the usage, the tense or the aspect (phase) of a word. Thus, the problem is posed that the decision burden is increased for selecting a translation.
Specifically, a plurality of example sentences having a different meaning than intended by the speaker are read and it is determined whether an ambiguity is contained in any part before selecting a correct example sentence. Thus, the decision burden is increased while at the same time posing the problem of a longer processing time required before selecting and proposing a correct translation to the other party.